by Cheng Siong Chin
Introduction Automate price monitoring for e-commerce competitors—ideal for retailers, analysts, and pricing teams. Scrapes competitor sites, extracts pricing/stock data via AI, detects changes, and sends instant alerts for dynamic pricing strategies. How It Works Scrapes competitor URLs via Firecrawl and Apify, extracts data with AI, detects price/stock changes, logs to Google Sheets, and sends Telegram alerts. Workflow Template Trigger → Scrape URL → AI Extract → Parse → Merge Historical → Detect Changes → Update Sheets + Send Telegram Alert Workflow Steps Trigger & Scrape → Manual/scheduled trigger → Firecrawl + Apify fetch competitor data AI Processing → Claude extracts product details → Parses and structures data Change Detection → Reads historical prices → Merges with current data → Identifies updates Output → Logs alerts to Sheets → Updates historical data → Sends Telegram notification Setup Instructions 1. Firecrawl API Get key from dashboard → Add to n8n 2. Apify API Get key from console → Add to n8n → Configure actors 3. AI Model (Claude/OpenAI) Get API key → Add to n8n 4. Google Sheets OAuth2 Create OAuth2 in Google Cloud Console → Authorize in n8n → Enable API 5. Telegram Bot Create via BotFather → Get token & chat ID → Add to n8n 6. Spreadsheet Setup Create Sheet with required columns → Copy ID → Paste in workflow Prerequisites Self-hosted n8n, Firecrawl account, Apify account, Claude/OpenAI API key, Google account (Sheets OAuth2),Telegram bot Customization Add more URLs, adjust scraping intervals, change detection thresholds, switch to Slack/email alerts, integrate databases Benefits Saves 2+ hours daily, real-time tracking, automated alerts, historical analysis, multi-source scraping
by Rahul Joshi
Description Gain real-time audience intelligence with this cross-platform AI Sentiment Analyzer for Twitter (X) and Facebook. 📊🧠 This workflow consolidates mentions and comments, performs GPT-4o-powered sentiment and keyword analysis, summarizes audience mood, highlights dominant trends, and sends a polished HTML report via email — all automatically. Ideal for marketing and insights teams tracking brand conversations across social platforms. 🚀💬 What This Template Does 1️⃣ Starts manually to fetch the latest Twitter mentions and Facebook post comments. 🕹️ 2️⃣ Merges both datasets into a unified JSON structure for seamless cross-platform analysis. 🧩 3️⃣ Validates incoming API data to ensure completeness before processing. ✅ 4️⃣ Runs a custom JavaScript transformation to normalize all messages and add sentiment placeholders. 🧠 5️⃣ Uses GPT-4o to perform sentiment and keyword trend analysis, returning structured JSON insights. 📈 6️⃣ Parses AI output to extract overall sentiment ratios and detailed post-level analysis. 🔍 7️⃣ Generates a human-readable HTML summary using GPT-4o — featuring emojis, bullet insights, and trend sections. 🎨 8️⃣ Emails the formatted sentiment report directly to the marketing team. ✉️ 9️⃣ Logs API or runtime errors automatically into Google Sheets for transparent monitoring. 🧾 Key Benefits ✅ Provides an automated end-to-end pipeline for sentiment intelligence. ✅ Centralizes Twitter and Facebook audience data in one workflow. ✅ Delivers structured insights ready for dashboards or client reporting. ✅ Generates branded HTML summaries that are ready for emailing. ✅ Improves reliability with built-in error tracking and validation layers. Features Dual-platform integration (Twitter X API + Facebook Graph API). JavaScript logic for merging and normalizing social datasets. GPT-4o-based sentiment classification and keyword extraction. Structured JSON parsing and visualization pipeline. AI-generated HTML summary reports for presentation and sharing. Automated email dispatch via Gmail. Google Sheets logging for audit and debugging. Modular configuration — easily extendable to other social networks. #3 Requirements Twitter OAuth2 credentials for fetching mentions. Facebook Graph API credentials for reading posts and comments. Azure OpenAI (GPT-4o) credentials for sentiment and summary generation. Gmail OAuth2 credentials for automated email delivery. Google Sheets OAuth2 credentials for error logging and tracking. Environment Variables TWITTER_API_KEY FACEBOOK_GRAPH_TOKEN AZURE_OPENAI_API_KEY GMAIL_REPORT_RECIPIENTS GOOGLE_SHEET_ERROR_LOG_ID Target Audience 📈 Marketing and insights teams monitoring audience engagement. 💬 Social media managers analyzing public sentiment. 🧠 Data analysts exploring brand perception trends. 💡 PR and communications teams managing online reputation. 🧾 Operations or automation teams integrating AI analytics into dashboards. Step-by-Step Setup Instructions 1️⃣ Connect all API credentials — Twitter, Facebook Graph, Azure OpenAI, Gmail, and Google Sheets. 2️⃣ Update your Twitter user ID and Facebook Page ID in the respective nodes. 3️⃣ Confirm the merge and validation logic in the Merge Platform Datasets and Validate API Response nodes. 4️⃣ Check that your Azure OpenAI account has GPT-4o access enabled. 5️⃣ Verify the Gmail recipient and test the “Send Email Summary” node for delivery. 6️⃣ Link your Google Sheet with a tab named error log sheet to capture workflow exceptions. 7️⃣ Run the workflow once manually to validate each layer — data, AI response, email delivery. 8️⃣ Optionally, schedule it to run daily or weekly for automated sentiment insights. ✅
by Cristina
Automated Weekly Newsletter with AI Research, Editorial Drafting, and Approval Flow This n8n template demonstrates how to automate the full production cycle of a professional weekly newsletter. It combines AI-powered market research, editorial drafting, compliance validation, and an approval loop — all before creating a final Gmail draft ready for distribution. Use cases are many: Wealth managers sending weekly market updates to clients Startups producing recurring research digests Teams creating automated newsletters for marketing or content distribution Good to know At time of writing, each AI call (research, editorial, QC) consumes API tokens from Perplexity and OpenAI. See provider pricing for updated info. Gmail integration requires OAuth setup with your account. You can adapt the prompts to any domain — from finance to tech to education. How it works Schedule Trigger runs every week and sets the date window. Research LLM fetches structured JSON market data using Perplexity. Editorial LLM transforms research into a polished ~2,000 word client-ready newsletter. QC LLM validates factual accuracy and compliance risks before approval. Preview Email is sent with Approve/Revise buttons. Clicking opens a secure n8n-hosted approval form. Final Draft Creation: Once approved, the workflow generates a clean Gmail draft, ready to send. How to use Replace the demo schedule trigger with your own (weekly, daily, or event-based). Set up Gmail OAuth credentials to enable email previews and final drafts. Update branding (logo, disclaimer, signature) in the HTML builder node. Adjust prompts to your audience — e.g., simplify tone for marketing, or keep institutional tone for financial clients. Requirements Perplexity account for research API (or your LLM of choice) OpenAI for editorial and QC steps (or your LLM of choice) Gmail account with OAuth credentials Optional: your own domain to host the approval webhook Customising this workflow This workflow can be extended beyond financial newsletters. Try: Content marketing: Automate weekly digests or trend reports Education: Generate curriculum summaries with approval loops for teachers Internal comms: Automate compliance-checked company updates
by Meelioo
How it works This beginner-friendly workflow demonstrates the core building blocks of n8n. It guides you through: Triggers – Start workflows manually, on a schedule, via webhooks, or through chat. Data processing** – Use Set and Code nodes to create, transform, and enrich data. Logic and branching – Apply conditions with IF nodes and merge different branches back together. API integrations** – Fetch external data (e.g., users from an API), split arrays into individual items, and extract useful fields. AI-powered steps** – Connect to OpenAI for generating fun facts or build interactive assistants with chat triggers, memory, and tools. Responses** – Return structured results via webhooks or summary nodes. By the end, it demonstrates a full flow: creating data → transforming it → making decisions → calling APIs → using AI → responding with outputs. Set up steps Time required: 5–10 minutes. What you need: An n8n instance (cloud or self-hosted). Optional: API credentials (e.g., OpenAI) if you want to test AI features. Setup flow: Import this workflow. Add your API keys where needed (OpenAI, etc.). Trigger the workflow manually or test with webhooks. >👉 Detailed node explanations and examples are already included as sticky notes inside the workflow itself, so you can learn step by step as you explore.
by LukaszB
UX & SEO Website Analyst (Airtop + OpenAI + Gmail) This workflow automatically analyzes a website for UX and SEO quality. It uses Airtop for realistic web scraping, OpenAI for structured evaluation of metadata (title, description, and overall SEO signals), and Gmail to send professional reports. What it does Scrapes website content and metadata through an Airtop session. Evaluates SEO and UX factors (strengths, weaknesses, recommendations) with OpenAI. Generates a clear, structured report. Sends the report automatically via Gmail. Use cases Marketing agencies auditing client websites. Freelancers offering SEO/UX review services. Businesses monitoring their own website performance. Requirements Airtop account** with API access. OpenAI API key**. Gmail credentials** connected in n8n. How it works Start the flow with a target website URL. Airtop opens a session and scrapes metadata naturally. OpenAI analyzes and scores the title, description, and overall quality. Gmail sends a formatted report to your chosen recipient. Set up steps Connect Airtop, OpenAI, and Gmail credentials in n8n. Provide the target URL to analyze. Run the workflow and review the email report. Keep detailed instructions inside sticky notes in the workflow.
by Ranjan Dailata
Who this is for This workflow is designed for teams that collect feedback or survey responses via Jotform and want to automatically: Analyze sentiment (positive, neutral, negative) of each response. Extract key topics and keywords from qualitative text. Generate AI summaries and structured insights. Store results in Google Sheets and n8n DataTables for easy reporting and analysis. Use Cases Customer experience analysis Market research & survey analysis Product feedback clustering Support ticket prioritization AI-powered blog or insight generation from feedback What this workflow does This n8n automation connects Jotform, Google Gemini, and Google Sheets to turn raw responses into structured insights with sentiment, topics, and keywords. Pipeline Overview Jotform → Webhook → Gemini (Topics + Keywords) → Gemini (Sentiment) → Output Parser → Merge → Google Sheets Jotform Trigger Captures each new submission from your Jotform (e.g., a feedback or survey form). Extracts raw fields ($json.body.pretty) such as name, email, and response text. Format Form Data (Code Node) Converts the Jotform JSON structure into a clean string for AI input. Ensures the text is readable and consistent for Gemini. Topics & Keyword Extraction (Google Gemini + Output Parser) Goal: Identify the main themes and important keywords from responses. { "topics": [ { "topic": "Product Features", "summary": "Users request more automation templates.", "keywords": ["AI templates", "automation", "workflow"], "sentiment": "positive", "importance_score": 0.87 } ], "global_keywords": ["AI automation", "developer tools"], "insights": ["Developers desire more creative, ready-to-use AI templates."], "generated_at": "2025-10-08T10:30:00Z" } Sentiment Analyzer (Google Gemini + Output Parser) Goal: Evaluate overall emotional tone and priority. { "customer_name": "Ranjan Dailata", "customer_email": "ranjancse@gmail.com", "feedback_text": "Please build more interesting AI automation templates.", "sentiment": "positive", "confidence_score": 0.92, "key_phrases": ["AI automation templates", "developer enablement"], "summary": "Customer requests more AI automation templates to boost developer productivity.", "alert_priority": "medium", "timestamp": "2025-10-08T10:30:00Z" } Merge + Aggregate Combines the topic/keyword extraction and sentiment output into a single structured dataset. Aggregates both results for unified reporting. Persist Results (Google Sheets) Writes combined output into your connected Google Sheet. Two columns recommended: feedback_analysis → Sentiment + Summary JSON topics_keywords → Extracted Topics + Keywords JSON Enables easy visualization, filtering, and reporting. Visualization (Optional) Add Sticky Notes or a logo image node in your workflow to: Visually describe sections (e.g., “Sentiment Analysis”, “Topic Extraction”). Embed brand logo: Example AI Output (Combined) { "feedback_analysis": { "customer_name": "Ranjan Dailata", "sentiment": "positive", "summary": "User appreciates current templates and suggests building more advanced AI automations.", "key_phrases": ["AI automation", "developer templates"] }, "topics_keywords": { "topics": [ { "topic": "AI Template Expansion", "keywords": ["AI automation", "workflow templates"], "sentiment": "positive", "importance_score": 0.9 } ], "global_keywords": ["automation", "AI development"] } } Setup Instructions Pre-requisite If you are new to Jotform, Please do signup using Jotform Signup For the purpose of demonstation, we are considering the Jotforms Prebuilt New Customer Registration Form as a example. However, you are free to consider for any of the form submissions. Step 0: Local n8n (Optional) If using local n8n, set up ngrok: ngrok http 5678 Use the generated public URL as your Webhook URL base for Jotform integration. Step 1: Configure the Webhook Copy the Webhook URL generated by n8n (e.g., /webhook-test/f3c34cda-d603-4923-883b-500576200322). You can copy the URL by double clicking on the Webhook node. Make sure to replace the base url with the above Step 0, if you are running the workflow from your local machine. In Jotform, go to your form → Settings → Integrations → Webhooks → paste this URL. Now, every new form submission will trigger the n8n workflow. Step 2: Connect Google Gemini Create a Google Gemini API Credential in n8n. Select the model models/gemini-2.0-flash-exp. Step 3: Create Data Storage Create a DataTable named JotformFeedbackInsights with columns: feedback_analysis (string) topics_keywords (string) Step 4: Connect Google Sheets Add credentials under Google Sheets OAuth2. Link to your feedback tracking sheet. Step 5: Test the Workflow Submit a form via Jotform. Check results: AI nodes return structured JSON. Google Sheet updates with new records. Customization Tips Change the Prompt You can modify the topic extraction prompt to highlight specific themes: You are a research analyst. Extract main topics, keywords, and actionable insights from this feedback: {{ $json.body }} Extend the Output Schema Add more fields like: { "suggested_blog_title": "", "tone": "", "recommendations": [] } Then update your DataTable or Sheets schema accordingly. Integration Ideas Send sentiment alerts to Slack for high-priority feedback. Push insights into Notion, Airtable, or HubSpot. Generate weekly reports summarizing trends across all submissions. Summary This workflow turns raw Jotform submissions into actionable insights using Google Gemini AI — extracting topics, keywords, and sentiment while automatically logging everything to Google Sheets.
by Punit
WordPress AI Content Creator Overview Transform a few keywords into professionally written, SEO-optimized WordPress blog posts with custom featured images. This workflow leverages AI to research topics, structure content, write engaging articles, and publish them directly to your WordPress site as drafts ready for review. What This Workflow Does Core Features Keyword-to-Article Generation**: Converts simple keywords into comprehensive, well-structured articles Intelligent Content Planning**: Uses AI to create logical chapter structures and content flow Wikipedia Integration**: Researches factual information to ensure content accuracy and depth Multi-Chapter Writing**: Generates coherent, contextually-aware content across multiple sections Custom Image Creation**: Generates relevant featured images using DALL-E based on article content SEO Optimization**: Creates titles, subtitles, and content optimized for search engines WordPress Integration**: Automatically publishes articles as drafts with proper formatting and featured images Business Value Content Scale**: Produce high-quality blog posts in minutes instead of hours Research Efficiency**: Automatically incorporates factual information from reliable sources Consistency**: Maintains professional tone and structure across all generated content SEO Benefits**: Creates search-engine friendly content with proper HTML formatting Cost Savings**: Reduces need for external content creation services Prerequisites Required Accounts & Credentials WordPress Site with REST API enabled OpenAI API access (GPT-4 and DALL-E models) WordPress Application Password or JWT authentication Public-facing n8n instance for form access (or n8n Cloud) Technical Requirements WordPress REST API v2 enabled (standard on most WordPress sites) WordPress user account with publishing permissions n8n instance with LangChain nodes package installed Setup Instructions Step 1: WordPress Configuration Enable REST API (usually enabled by default): Check that yoursite.com/wp-json/wp/v2/ returns JSON data If not, contact hosting provider or install REST API plugin Create Application Password: In WordPress Admin: Users > Profile Scroll to "Application Passwords" Add new password with name "n8n Integration" Copy the generated password (save securely) Get WordPress Site URL: Note your full WordPress site URL (e.g., https://yourdomain.com) Step 2: OpenAI Configuration Obtain OpenAI API Key: Visit OpenAI Platform Create API key with access to: GPT-4 models (for content generation) DALL-E (for image creation) Add OpenAI Credentials in n8n: Navigate to Settings > Credentials Add "OpenAI API" credential Enter your API key Step 3: WordPress Credentials in n8n Add WordPress API Credentials: In n8n: Settings > Credentials > "WordPress API" URL: Your WordPress site URL Username: Your WordPress username Password: Application password from Step 1 Step 4: Update Workflow Settings Configure Settings Node: Open the "Settings" node Replace wordpress_url value with your actual WordPress URL Keep other settings as default or customize as needed Update Credential References: Ensure all WordPress nodes reference your WordPress credentials Verify OpenAI nodes use your OpenAI credentials Step 5: Deploy Form (Production Use) Activate Workflow: Toggle workflow to "Active" status Note the webhook URL from Form Trigger node Test Form Access: Copy the form URL Test form submission with sample data Verify workflow execution completes successfully Configuration Details Form Customization The form accepts three key inputs: Keywords**: Comma-separated topics for article generation Number of Chapters**: 1-10 chapters for content structure Max Word Count**: Total article length control You can modify form fields by editing the "Form" trigger node: Add additional input fields (category, author, publish date) Change field types (dropdown, checkboxes, file upload) Modify validation rules and requirements AI Content Parameters Article Structure Generation The "Create post title and structure" node uses these parameters: Model**: GPT-4-1106-preview for enhanced reasoning Max Tokens**: 2048 for comprehensive structure planning JSON Output**: Structured data for subsequent processing Chapter Writing The "Create chapters text" node configuration: Model**: GPT-4-0125-preview for consistent writing quality Context Awareness**: Each chapter knows about preceding/following content Word Count Distribution**: Automatically calculates per-chapter length Coherence Checking**: Ensures smooth transitions between sections Image Generation Settings DALL-E parameters in "Generate featured image": Size**: 1792x1024 (optimized for WordPress featured images) Style**: Natural (photographic look) Quality**: HD (higher quality output) Prompt Enhancement**: Adds photography keywords for better results Usage Instructions Basic Workflow Access the Form: Navigate to the form URL provided by the Form Trigger Enter your desired keywords (e.g., "artificial intelligence, machine learning, automation") Select number of chapters (3-5 recommended for most topics) Set word count (1000-2000 words typical) Submit and Wait: Click submit to trigger the workflow Processing takes 2-5 minutes depending on article length Monitor n8n execution log for progress Review Generated Content: Check WordPress admin for new draft post Review article structure and content quality Verify featured image is properly attached Edit as needed before publishing Advanced Usage Custom Prompts Modify AI prompts to change: Writing Style**: Formal, casual, technical, conversational Target Audience**: Beginners, experts, general public Content Focus**: How-to guides, opinion pieces, news analysis SEO Strategy**: Keyword density, meta descriptions, heading structure Bulk Content Creation For multiple articles: Create separate form submissions for each topic Schedule workflow executions with different keywords Use CSV upload to process multiple keyword sets Implement queue system for high-volume processing Expected Outputs Article Structure Generated articles include: SEO-Optimized Title**: Compelling, keyword-rich headline Descriptive Subtitle**: Supporting context for the main title Introduction**: ~60 words introducing the topic Chapter Sections**: Logical flow with HTML formatting Conclusions**: ~60 words summarizing key points Featured Image**: Custom DALL-E generated visual Content Quality Features Factual Accuracy**: Wikipedia integration ensures reliable information Proper HTML Formatting**: Bold, italic, and list elements for readability Logical Flow**: Chapters build upon each other coherently SEO Elements**: Optimized for search engine visibility Professional Tone**: Consistent, engaging writing style WordPress Integration Draft Status**: Articles saved as drafts for review Featured Image**: Automatically uploaded and assigned Proper Formatting**: HTML preserved in WordPress editor Metadata**: Title and content properly structured Troubleshooting Common Issues "No Article Structure Generated" Cause: AI couldn't create valid structure from keywords Solutions: Use more specific, descriptive keywords Reduce number of chapters requested Check OpenAI API quotas and usage Verify keywords are in English (default language) "Chapter Content Missing" Cause: Individual chapter generation failed Solutions: Increase max tokens in chapter generation node Simplify chapter prompts Check for API rate limiting Verify internet connectivity for Wikipedia tool "WordPress Publication Failed" Cause: Authentication or permission issues Solutions: Verify WordPress credentials are correct Check WordPress user has publishing permissions Ensure WordPress REST API is accessible Test WordPress URL accessibility "Featured Image Not Attached" Cause: Image generation or upload failure Solutions: Check DALL-E API access and quotas Verify image upload permissions in WordPress Review image file size and format compatibility Test manual image upload to WordPress Performance Optimization Large Articles (2000+ words) Increase timeout values in HTTP request nodes Consider splitting very long articles into multiple posts Implement progress tracking for user feedback Add retry mechanisms for failed API calls High-Volume Usage Implement queue system for multiple simultaneous requests Add rate limiting to respect OpenAI API limits Consider batch processing for efficiency Monitor and optimize token usage Customization Examples Different Content Types Product Reviews Modify prompts to include: Pros and cons sections Feature comparisons Rating systems Purchase recommendations Technical Tutorials Adjust structure for: Step-by-step instructions Code examples Prerequisites sections Troubleshooting guides News Articles Configure for: Who, what, when, where, why structure Quote integration Fact checking emphasis Timeline organization Alternative Platforms Replace WordPress with Other CMS Ghost**: Use Ghost API for publishing Webflow**: Integrate with Webflow CMS Strapi**: Connect to headless CMS Medium**: Publish to Medium platform Different AI Models Claude**: Replace OpenAI with Anthropic's Claude Gemini**: Use Google's Gemini for content generation Local Models**: Integrate with self-hosted AI models Multiple Models**: Use different models for different tasks Enhanced Features SEO Optimization Add nodes for: Meta Description Generation**: AI-created descriptions Tag Suggestions**: Relevant WordPress tags Internal Linking**: Suggest related content links Schema Markup**: Add structured data Content Enhancement Include additional processing: Plagiarism Checking**: Verify content originality Readability Analysis**: Assess content accessibility Fact Verification**: Multiple source confirmation Image Optimization**: Compress and optimize images Security Considerations API Security Store all credentials securely in n8n credential system Use environment variables for sensitive configuration Regularly rotate API keys and passwords Monitor API usage for unusual activity Content Moderation Review generated content before publishing Implement content filtering for inappropriate material Consider legal implications of auto-generated content Maintain editorial oversight and fact-checking WordPress Security Use application passwords instead of main account password Limit WordPress user permissions to minimum required Keep WordPress and plugins updated Monitor for unauthorized access attempts Legal and Ethical Considerations Content Ownership Understand OpenAI's terms regarding generated content Consider copyright implications for Wikipedia-sourced information Implement proper attribution where required Review content licensing requirements Disclosure Requirements Consider disclosing AI-generated content to readers Follow platform-specific guidelines for automated content Ensure compliance with advertising and content standards Respect intellectual property rights Support and Maintenance Regular Maintenance Monitor OpenAI API usage and costs Update AI prompts based on output quality Review and update Wikipedia search strategies Optimize workflow performance based on usage patterns Quality Assurance Regularly review generated content quality Implement feedback loops for improvement Test workflow with diverse keyword sets Monitor WordPress site performance impact Updates and Improvements Stay updated with OpenAI model improvements Monitor n8n platform updates for new features Engage with community for workflow enhancements Document custom modifications for future reference Cost Optimization OpenAI Usage Monitor token consumption patterns Optimize prompts for efficiency Consider using different models for different tasks Implement usage limits and budgets Alternative Approaches Use local AI models for cost reduction Implement caching for repeated topics Batch similar requests for efficiency Consider hybrid human-AI content creation License and Attribution This workflow template is provided under MIT license. Attribution to original creator appreciated when sharing or modifying. Generated content is subject to OpenAI's usage policies and terms of service.
by Ruthwik
📧 AI-Powered Email Categorization & Labeling in Zoho Mail This n8n template demonstrates how to use AI text classification to automatically categorize incoming emails in Zoho Mail and apply the correct label (e.g., Support, Billing, HR). It saves time by keeping your inbox structured and ensures emails are routed to the right category. Use cases include: Routing customer support requests to the correct team. Organizing billing and finance communications separately. Streamlining HR and recruitment email handling. Reducing inbox clutter and ensuring no important message is missed. ℹ️ Good to know You’ll need to configure Zoho OAuth credentials — see Self Client Overview, Authorization Code Flow, and Zoho Mail OAuth Guide. The labels must already exist in Zoho Mail (e.g., Support, Billing, HR). The workflow fetches these labels and applies them automatically. The Zoho Mail API domain changes depending on your account region: .com → Global accounts (https://mail.zoho.com/api/...) .eu → EU accounts (https://mail.zoho.eu/api/...) .in → India accounts (https://mail.zoho.in/api/...) Example: For an EU account, the endpoint would be: https://mail.zoho.eu/api/accounts/<accountID>/updatemessage The AI model used for text classification may incur costs depending on your provider (e.g., OpenRouter). Start by testing with a small set of emails before enabling for your full inbox. 🔄 How it works A new email in Zoho Mail triggers the workflow. OAuth authentication retrieves access to Zoho Mail’s API. All available labels are fetched, and a label map (display name → ID) is created. The AI model analyzes the subject and body to predict the correct category. The workflow routes the email to the right category branch. The matching Zoho Mail label is applied (final node is deactivated by default). 🛠️ How to use Create the required labels (e.g., Support, Billing, HR, etc.) in your Zoho Mail account before running the workflow. Replace the Zoho Mail Account ID in the Set Account ID node. Configure your Zoho OAuth credentials in the Get Access Token node. Update the API base URL to match your Zoho account’s region (.com, .eu, .in, etc.). Activate the Apply Label to Email node once ready for production. Optionally, adjust categories in the AI classifier prompt to fit your organization’s needs. 📋 Requirements Zoho Mail account with API access enabled. Labels created in Zoho Mail for each category you want to classify. OAuth credentials set up in n8n. Correct Zoho Mail API domain (.com, .eu, .in) based on your account region. An AI model (via OpenRouter or other provider) for text classification. 🎨 Customising this workflow This workflow can be adapted to many inbox management scenarios. Examples include: Auto-routing customer inquiries to specific departments. Prioritizing VIP client emails with special labels. Filtering job applications directly into an HR-managed folder.
by Yasser Sami
Customer Support AI Agent for Gmail This n8n template demonstrates how to build an AI-powered customer support workflow that automatically handles incoming Gmail messages, classifies them, finds answers from your knowledge base, and sends a personalized reply. Who’s it for SaaS founders or teams who want to automate customer support. Freelancers and solopreneurs who receive repetitive customer queries. Companies that want to reduce manual email triage and improve response times. How it works / What it does Trigger: A new email arrives in Gmail. Classification: The workflow uses a text classifier to decide whether the email is customer support-related or not. If not, it’s ignored. If yes, it proceeds. AI Agent: Queries a knowledge base (vector database with OpenAI embeddings). Retrieves the most relevant answer. Drafts a reply using AI (OpenAI or Google Gemini model). Post-processing: Labels the email in Gmail for organization. Sends a reply automatically. This ensures that your customers get timely, relevant responses without manual intervention. How to set up Import this template into your n8n account. Connect your Gmail account in the Gmail Trigger, Label, and Reply nodes. Connect your AI model provider (OpenAI or Google Gemini). Configure the knowledge base embeddings (upload your docs/FAQ into the vector database). Activate the workflow — and your AI customer support agent is live! Requirements n8n account. Gmail account (with API access enabled). OpenAI or Google Gemini account for LLM and embeddings. Knowledge base data (FAQ, documentation, or past tickets). Google Drive account for auto update your vector database(with API access enabled). How to customize the workflow Knowledge Base**: Replace or expand with your own company docs, FAQs, or past conversations. Classification Rules**: Train or adjust the classifier to handle more categories (e.g., Sales, Partnership, Technical Support). Reply Style**: Customize AI prompts for tone — professional, casual, or friendly. Labels**: Change Gmail labels to match your workflow (e.g., “Support,” “Sales,” “Priority”). Multi-language**: Add translation steps if your customers speak different languages. This template saves you hours of manual email triage and ensures your customers always get quick, accurate responses.
by Kev
Generate ready-to-publish short-form videos from text prompts using AI Click on the image to see the Example output in google drive Transform simple text concepts into professional short-form videos complete with AI-generated visuals, narrator voice, background music, and dynamic text overlays - all automatically generated and ready for Instagram, TikTok, or YouTube Shorts. This workflow demonstrates a cost-effective approach to video automation by combining AI-generated images with audio composition instead of expensive AI video generation. Processing takes 1-2 minutes and outputs professional 9:16 vertical videos optimized for social platforms. The template serves as both a showcase and building block for larger automation systems, with sticky notes providing clear guidance for customization and extension. Who's it for Content creators, social media managers, and marketers who need consistent, high-quality video content without manual production work. Perfect for motivational content, storytelling videos, educational snippets, and brand campaigns. How it works The workflow uses a form trigger to collect video theme, setting, and style preferences. ChatGPT generates cohesive scripts and image prompts, while Google Gemini creates themed background images and OpenAI TTS produces narrator audio. Background music is sourced from Openverse for CC-licensed tracks. All assets are uploaded to JsonCut API which composes the final video with synchronized overlays, transitions, and professional audio mixing. Results are stored in NocoDB for management. How to set up JsonCut API: Sign up at jsoncut.com and create an API key at app.jsoncut.com. Configure HTTP Header Auth credential in n8n with header name x-api-key OpenAI API: Set up credentials for script generation and text-to-speech Google Gemini API: Configure access for Imagen 4.0 image generation NocoDB (Optional): Set up instance for video storage and configure database credentials Requirements JsonCut free account with API key OpenAI API access for GPT and TTS Google Gemini API for image generation NocoDB (optional) for result storage How to customize the workflow This template is designed as a foundation for larger automation systems. The modular structure allows easy modification of AI prompts for different content niches (business, wellness, education), replacement of the form trigger with RSS feeds or database triggers for automated content generation, integration with social media APIs for direct publishing, and customization of visual branding through JsonCut configuration. The workflow can be extended for bulk processing, A/B testing multiple variations, or integration with existing content management systems. Sticky notes throughout the workflow provide detailed guidance for common customizations and scaling options.
by Marco Venturi
How it works This workflow sources news from news websites. The information is then passed to an LLM, which processes the article's content. An editor approves or rejects the article. If accepted, the article is first published on the WordPress site and then on the LinkedIn page. Setup Instructions 1. Credentials You'll need to add credentials for the following services in your n8n instance: News API**: A credential for your chosen news provider. LLM**: Your API key for the LLM you want to use. Google OAuth**: For both Gmail and Google Sheets. WordPress OAuth2**: To publish articles via the API. See the WordPress Developer Docs. LinkedIn OAuth2**: To share the post on a company page. 2. Node Configuration Don't forget to: Fetch News (HTTP Request)**: Set the query parameters (keywords, language, etc.) for your news source. Basic LLM Chain: Review and **customize the prompt to match your desired tone, language, and style. Approval request (Gmail)**: Set your email address in the Send To field. HTTP Request WP - Push article**: Replace <site_Id> in the URL with your WordPress Site ID. getImageId (Code Node)**: Update the array with your image IDs from the WordPress Media Library. Create a post (LinkedIn)**: Enter your LinkedIn Organization ID. Append row in sheet (Google Sheets)**: Select your Google Sheet file and the target sheet. All Email Nodes**: Make sure the Send To field is your email.
by Lucas Peyrin
How it works This workflow creates a sophisticated, self-improving customer support system that automatically handles incoming emails. It's designed to answer common questions using an AI-powered knowledge base and, crucially, to learn from human experts when new or complex questions arise, continuously expanding its capabilities. Think of it like having an AI assistant with a smart memory and a human mentor. Here's the step-by-step process: New Email Received: The workflow is triggered whenever a new email arrives in your designated support inbox (via Gmail). Classify Request: An AI model (Google Gemini 2.5 Flash Lite) first classifies the incoming email to ensure it's a genuine support request, filtering out irrelevant messages. Retrieve Knowledge Base: The workflow fetches all existing Question and Answer pairs from your dedicated Google Sheet knowledge base. AI Answer Attempt: A powerful AI model (Google Gemini 2.5 Pro) analyzes the customer's email against the entire knowledge base. It attempts to find a highly relevant answer and drafts a complete HTML email response if successful. Decision Point: An IF node checks if the AI found a confident answer. If Answer Found: The AI-generated HTML response is immediately sent back to the customer via Gmail. If No Answer Found (Human-in-the-Loop): Escalate to Human: The customer's summarized question and original email are forwarded to a human expert (you or your team) via Gmail, requesting their assistance. Human Reply & AI Learning: The workflow waits for the human expert's reply. Once received, another AI model (Google Gemini 2.5 Flash) processes both the original customer question and the expert's reply to distill them into a new, generic, and reusable Question/Answer pair. Update Knowledge Base: This newly created Q&A pair is then automatically added as a new row to your Google Sheet knowledge base, ensuring the system can answer similar questions automatically in the future. Set up steps Setup time: ~10-15 minutes This workflow requires connecting your Gmail and Google Sheets accounts, and obtaining a Google AI API key. Follow these steps carefully: Connect Your Gmail Account: Select the On New Email Received node. Click the Credential dropdown and select + Create New Credential to connect your Gmail account. Grant the necessary permissions. Repeat this for the Send AI Answer and Ask Human for Help nodes, selecting the credential you just created. Connect Your Google Sheets Account: Select the Get Knowledge Base node. Click the Credential dropdown and select + Create New Credential to connect your Google account. Grant the necessary permissions. Repeat this for the Add to Knowledge Base node, selecting the credential you just created. Set up Your Google Sheet Knowledge Base: Create a new Google Sheet in your Google Drive. Rename the first sheet (tab) to QA Database. In the first row of QA Database, add two column headers: Question (in cell A1) and Answer (in cell B1). Go back to the Get Knowledge Base node in n8n. In the Document ID field, select your newly created Google Sheet. Do the same for the Add to Knowledge Base node. Get Your Google AI API Key (for Gemini Models): Visit Google AI Studio at aistudio.google.com/app/apikey. Click "Create API key in new project" and copy the key. In the workflow, go to the Google Gemini 2.5 Pro node, click the Credential dropdown, and select + Create New Credential. Paste your key into the API Key field and Save. Repeat this for the Google Gemini 2.5 Flash Lite and Google Gemini 2.5 Flash nodes, selecting the credential you just created. Configure Human Expert Email: Select the Ask Human for Help node. In the Send To field, replace the placeholder email address with the actual email address of your human expert (e.g., your own email or a team support email). Activate the Workflow: Once all credentials and configurations are set, activate the workflow using the toggle switch at the top right of your n8n canvas. Start Learning! Send a test email to the Gmail account connected to the On New Email Received node. Observe how the AI responds, or how it escalates to your expert email and then learns from the reply. Check your Google Sheet to see new Q&A pairs being added!